Information may be conveyed through a variety of mediums. For decades, printed media such as newspapers and/or magazines were used to convey information to a multitude of people. Now, the Internet makes it possible to convey information through many forms of electronic media.
Web-sites are a common way to convey information over the Internet. Additional forms of electronically conveying information have developed and taken off in the past few years. Blogs and social media/networking web-sites allow users less proficient with computers to log-on and convey their opinion about people, companies, products, or anything that may be of interest.
As easily as information can be transmitted over the Internet, the very same information can be monitored and analyzed. Sentiment analysis technology analyzes information presented in both electronic and non-electronic media in order to help determine a particular viewpoint or opinion about a particular topic.
For example, an individual may log on to Facebook® and post a message about how much they like a new product. Sentiment analysis technology can retrieve and store the user's post and determine that the user's sentiment towards the new product is positive.
Current sentiment analysis technology typically acquires mass volumes of social media data and stores the data in a relational database. The data can later be retrieved for sentiment analysis, and individuals and/or corporations can determine the overall sentiment about a topic based on the collected and analyzed data.
Unfortunately, these systems do not efficiently process the mass volumes of data that must be collected and organized in a relational database before sentiment analysis can be performed and before the data can be customized for a particular person and/or entity. Thus, there is a need for a system that quickly and efficiently analyzes large volumes of social media data for sentiment and stores it in a database for post-analysis by a particular individual and/or entity.